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A Comprehensive Evaluation Framework for Language Models
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overview
HELM Benchmark offers a holistic evaluation of language models through a set of well-curated, multi-metric datasets. It empowers researchers and developers to understand model capabilities beyond simple performance measures.
features
With its advanced features, HELM Benchmark redefines how language models are evaluated. It prioritizes comprehensive, fair assessments that are aligned with actual use cases.
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HELM Benchmark is designed for a wide range of users, including researchers looking for thorough assessments, AI developers in pursuit of fine-tuning models, and organizations seeking reliable evaluations for production deployment.
HELM Benchmark stands out by offering a holistic evaluation approach, focusing on mean scenario scores while ensuring transparency and reproducibility across evaluations.
The leaderboards are maintained by a dedicated team of researchers and AI experts, ensuring that they reflect the latest advancements and model performances accurately.
Getting started is easy! Visit our website at https://crfm.stanford.edu/helm to explore the resources available and dive into the evaluation framework.